sql server - Selecting records for deletions based on relationship with previous and next records -


i have sql server 2014 table millions of gps coordinates, each @ particular time. interval between registrations not fixed , varies 1 second couple of hours. want keep 1 measurement every 4 minutes, other records have deleted.

i tried while loop in t-sql traverses every record, inside loop select statement double cross apply return record if sits in beween 2 other records not more 4 minutes apart. strategy turns out slow.

can done set-based solution ? or there way speed-up query ? (the test query below printing, not yet deleting)

select * #mytemp gps order timepoint asc   declare @id uniqueidentifier declare @d1 varchar(19) declare @d2 varchar(19) declare @d3 varchar(19)   while exists (select * #mytemp ) begin     select top 1 @id = id #mytemp order timepoint asc      select          @d1 = convert(varchar(19), a.justbefore, 121),          @d2 = convert(varchar(19), b.tijdstip, 121),         @d3 = convert(varchar(19), c.justafter, 121)     gps b cross apply          (             select  top 1 timepoint justbefore             gps                (b.timepoint > timepoint ) , (b.id = @id )             order timepoint desc          )          cross apply (             select  top 1 timepoint justafter             gps               (datediff(n,a.justbefore,timepoint ) between -4 , 0)                      , (b.timepoint < timepoint )             order timepoint asc         ) c      print 'id=' + cast(@id varchar(50))                  + ' / d1=' + @d1 + ' / d2=' + @d2 + ' / d3=' + @d3                         delete #mytemp id = @id    end

--

 sample data:     id     timepoint            lat      lon     1      20170725 13:05:27    12,256   24,123     2      20170725 13:10:27    12,254   24,120     3      20170725 13:10:29    12,253   24,125       4      20170725 13:11:55    12,259   24,127     5      20170725 13:11:59    12,255   24,123     6      20170725 13:14:28    12,254   24,126     7      20170725 13:16:52    12,259   24,121     8      20170725 13:20:53    12,257   24,125

in case records 3,4,5 should deleted. record 7 should stay gap between 7 , 8 longer 4 minutes.

looking @ numbers... looks 1 & 2 stay (5 mins apart)...3, 4, & 5 should go... 6 stays (4 mins 2)... 7 should go (only 2 mins 6) , 8 stays (6 mins 6)...

if correct, following you're looking for...   if object_id('tempdb..#testdata', 'u') not null  drop table #testdata;  create table #testdata (     id int not null primary key clustered,     timepoint datetime2(0) not null,     lat decimal(9,3),     lon decimal(9,3)     );    insert #testdata (id, timepoint, lat, lon) values     (1, '20170725 13:05:27', 12.256, 24.123),     (2, '20170725 13:10:27', 12.254, 24.120),     (3, '20170725 13:10:29', 12.253, 24.125),       (4, '20170725 13:11:55', 12.259, 24.127),     (5, '20170725 13:11:59', 12.255, 24.123),     (6, '20170725 13:14:28', 12.254, 24.126),     (7, '20170725 13:16:52', 12.259, 24.121),     (8, '20170725 13:20:53', 12.257, 24.125);  --  select * #testdata td;  --================================================================================       cte_addlag (         select              td.id, td.timepoint, td.lat, td.lon,             minfromprev = datediff(mi, lag(td.timepoint, 1) on (order td.timepoint), td.timepoint)                     #testdata td         ),     cte_timegroup (         select              *,             timegroup = isnull(sum(al.minfromprev) on (order al.timepoint rows unbounded preceding) / 4, 0)                     cte_addlag al         ) select top 1 ties      tg.id,      tg.timepoint,      tg.lat,      tg.lon     cte_timegroup tg order      row_number() on (partition tg.timegroup order tg.timepoint);

results...

id          timepoint                   lat                                     lon ----------- --------------------------- --------------------------------------- --------------------------------------- 1           2017-07-25 13:05:27         12.256                                  24.123 2           2017-07-25 13:10:27         12.254                                  24.120 6           2017-07-25 13:14:28         12.254                                  24.126 8           2017-07-25 13:20:53         12.257                                  24.125

hth, jason


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